Principal AI Engineer, United Kingdom

As a Principal AI Engineer at BJAK, your role includes leading and mentoring a skilled team of AI engineers while collaborating with product stakeholders to establish project goals. You will design and implement AI models to tackle complex business problems, manage the AI model lifecycle from data collection to deployment, and drive analytics for informed decision-making. Staying updated on AI advancements and applying cutting-edge techniques will also be part of your day-to-day responsibilities.

To qualify for the Principal AI Engineer role at BJAK, candidates should possess a Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field. Proven experience as an AI engineer or data scientist is crucial, particularly a strong track record in leading successful AI projects. Proficiency in AI frameworks, programming languages like Python, and expertise in data preprocessing and model evaluation are also essential.

At BJAK, the work environment is dynamic and fast-paced, designed for those who thrive on challenges. Our flat organizational structure fosters an atmosphere of collaboration and ownership, where innovative ideas are encouraged. As a Principal AI Engineer, you'll enjoy the autonomy to make impactful decisions while being part of an international team passionate about AI and machine learning.

BJAK is dedicated to the professional growth of its employees, offering strong learning and development plans tailored for a Principal AI Engineer. As you contribute meaningfully to our projects, you'll find ample opportunities for career advancement. Whether through leadership roles or specialized training in AI and machine learning, your path to growth here is as limitless as your ambition.

In the role of Principal AI Engineer at BJAK, you'll engage in groundbreaking projects that focus on developing AI solutions designed to simplify tasks and enhance productivity. Your work may involve creating intelligent task automation systems and tackling complex business challenges using advanced algorithms and machine learning models, ensuring that our AI solutions are practical, scalable, and impactful.

When answering this question, focus on specific examples of AI models you've developed, including the tools and frameworks you used. Highlight the challenges you faced during development and how you overcame them, demonstrating your hands-on experience and problem-solving skills.

Discuss your engagement with the AI community, whether through research papers, online courses, conferences, or forums. Share specific resources you follow and any recent innovations you've implemented in your projects to illustrate your commitment to continuous learning.

In your response, emphasize the importance of clear communication and building trust within your team. Talk about how you foster a collaborative environment and encourage initiative, while also supporting your team's growth through mentoring and constructive feedback.

Explain your process for data preprocessing, including techniques you use for data cleaning, normalization, and feature engineering. Provide examples of how effective preprocessing has enhanced model performance in your past projects.

Enumerate the specific AI frameworks and programming languages you're proficient in, like TensorFlow, PyTorch, and Python. Provide examples of projects where you've applied these tools, showcasing your technical expertise.

Share a detailed story of an intricate AI challenge you've encountered, outlining the problem, your approach to finding a solution, and the eventual outcome. This illustrates your analytical thinking and ability to work through difficult situations.

Discuss your approach to building scalable AI systems, touching on aspects like infrastructure, code optimization, and data management. Provide examples where you successfully scaled a project to handle increasing demands.

Highlight qualities such as leadership, technical expertise, problem-solving skills, and the ability to communicate effectively across teams. Relate these qualities back to your values and how they align with BJAK’s mission.

Explain your strategy for incorporating data analytics within your AI projects, detailing how analytics inform decision-making and project direction. Use examples to show how analytics have enhanced the insights derived from your AI solutions.

Discuss your passion for AI and its potential to create impactful solutions. Share specific areas of AI that excite you and describe how your motivation drives you to innovate and contribute positively to the field.